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Background: Gastric cardia adenocarcinoma (GCA) is a highly fatal form of cancer in humans. The aim of this study was to extract clinicopathological data of postoperative patients with GCA from the Surveillance, Epidemiology, and End Results database, analyze prognostic risk factors, and build a nomogram. Methods: In this study, the clinical information of 1448 patients with GCA who underwent radical surgery and were diagnosed between 2010 and 2015 was extracted from the SEER database. The patients were then randomly divided into training (n = 1013) and internal validation (n = 435) cohorts at a 7:3 ratio. The study also included an external validation cohort (n = 218) from a Chinese hospital. The study used the Cox and LASSO models to pinpoint the independent risk factors linked to GCA. The prognostic model was constructed according to the results of the multivariate regression analysis. To assess the predictive accuracy of the nomogram, four methods were used: C-index, calibration curve, timedependent ROC curve, and DCA curve. Kaplan-Meier survival curves were also generated to illustrate the differences in cancer-specific survival (CSS) between the groups. Results: The results of the multivariate Cox regression analysis showed that age, grade, race, marital status, T stage, and log odds of positive lymph nodes (LODDS) were independently associated with cancer-specific survival in the training cohort. Both the C-index and AUC values depicted in the nomogram were greater than 0.71. The calibration curve revealed that the nomogram's CSS prediction was consistent with the actual outcomes. The decision curve analysis suggested moderately positive net benefits. Based on the nomogram risk score, significant differences in survival between the high-and low-risk groups were observed. How to cite this article: Wang L, Ge J, Feng L, et al. Establishment and validation of a prognostic nomogram for postoperative patients with gastric cardia adenocarcinoma: A study based on the Surveillance, Epidemiology, and End Results database and a Chinese cohort.

ObjectiveThe prognostic nutritional index (PNI) is an important prognostic factor for survival outcomes in various hematological malignancies. The current study focused on exploring the predictive value of the PNI in newly diagnosed follicular lymphoma (FL) in China.Materials and methodsThe clinical indicators and follow-up data of 176 patients who received chemotherapy or immunotherapy combined with chemotherapy with FL in our hospital from January 2016 to March 2022 were retrospectively analyzed. Cox proportional hazard model was used for univariate and multivariate analyses. Kaplan–Meier curves were used to calculate survival rates and draw survival curves. The log-rank test was applied to compare differences between groups.ResultsThe optimal cut-off value of PNI was 44.3. All patients were divided into a high PNI group (>44.3) and a low PNI group (≤44.3). The low PNI group had a low CR rate and a high risk of death, with a tendency toward POD24, and Both OS and PFS were worse than those in the high PNI group. PNI was able to predict OS and PFS in FL patients and was the only independent predictor of OS (P = 0.014 HR 5.024; 95%CI 1.388∼18.178) in multivariate analysis. PNI could re-stratify patients into groups of high FLIPI score, high FLIPI2 score, no POD24, and rituximab combined with chemotherapy. Moreover, integrating PNI into the FLIPI and FLIPI2 models improved the area under the curve (AUC) for more accurate survival prediction and prognosis.ConclusionPNI is a significant prognostic indicator for newly diagnosed FL in China that can early identify patients with poor prognosis and guide clinical treatment decisions.

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Epigenetic regulation plays a crucial part in the oncogenesis and treatment of diffuse large B-cell lymphoma (DLBCL). The H3K9me3-specific histone methyltransferase SUV39H1 is a significantly epigenetic gene that promotes the progression of a variety of malignancies. However, the roles of SUV39H1 in DLBCL remain unclear. By retrieving Oncomine, GEPIA, CCLE, UALCAN, and TCGA databases, we observed that the expression of SUV39H1 was higher in DLBCL tissues than in normal and other cancer tissues. Combined with immunohistochemical validation assay, we analysed clinical characteristics of DLBCL patients. The results showed that high expression of SUV39H1 was closely associated with age over 50 years old (P=0.014) and low albumin level (P=0.015). In the prognostic analyses, DLBCL patients in GEPIA database showed that the high SUV39H1 expression group had a lower disease-free survival (DFS) rate than the low SUV39H1 expression group (P=0.035). Finally, we discovered that expressions of CD86+ and CD163+ macrophages have high correlations with SUV39H1+ in DLBCL tissues(with P=0.037 and P=0.045,respectively). SUV39H1-associated macrophages may downregulate T lymphocyte subsets, especially Treg cells in DLBCL(P=0.003). In summary, SUV39H1 might be not only a potential target for the epigenetic therapy and immunotherapy of DLBCL, but also a clinical indicator for doctors to evaluate the trend of disease development.